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326
Financial Incentives and Student Achievement: Evidence from Randomized Trials.” Working paper
, 2010
"... Didear (Dallas), for their endless cooperation in collecting the data necessary for this project. I am indebted to ..."
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Cited by 73 (1 self)
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Didear (Dallas), for their endless cooperation in collecting the data necessary for this project. I am indebted to
Causal inference in statistics: An Overview
, 2009
"... This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all ca ..."
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Cited by 61 (12 self)
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This review presents empirical researcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interventions, (also called “causal effects ” or “policy evaluation”) (2) queries about probabilities of counterfactuals, (including assessment of “regret, ” “attribution” or “causes of effects”) and (3) queries about direct and indirect effects (also known as “mediation”). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both.
Energy Conservation "Nudges" and Environmentalist Ideology: Evidence From a Randomized Residential Electricity Field Experiment, NBER Working Paper 15939
, 2010
"... We thank Maximilian Auffhammer, the participants at the 2010 POWER Conference, and seminar participants at Princeton for comments. We thank the UCLA Ziman Real Estate Center for funding. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bure ..."
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Cited by 51 (0 self)
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We thank Maximilian Auffhammer, the participants at the 2010 POWER Conference, and seminar participants at Princeton for comments. We thank the UCLA Ziman Real Estate Center for funding. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
The experimental approach to development economics
- Ann Rev Econ
"... Randomized experiments have become a popular tool in development economics research, and have been the subject of a number of criticisms. This paper reviews the recent literature, and discusses the strengths and limitations of this approach in theory and in practice. We argue that the main virtue of ..."
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Cited by 47 (1 self)
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Randomized experiments have become a popular tool in development economics research, and have been the subject of a number of criticisms. This paper reviews the recent literature, and discusses the strengths and limitations of this approach in theory and in practice. We argue that the main virtue of randomized experiments is that, due to the close collaboration between researchers and implementers, they allow the estimation of parameters that it would not otherwise be possible to evaluate. We discuss the concerns that have been raised regarding experiments, and generally conclude that while they are real, they are often not specific to experiments. We conclude by discussing the relationship between theory and experiments. The last few years have seen a veritable explosion of randomized experiments in development economics and with it, perhaps inevitably, a rising tide of criticism. Almost all of the criticism is well-meant, recognizing the benefits of such experiments while suggesting that we not forget that there are a lot of important questions that randomized experiments cannot answer. Much of it is also not new. Indeed, most of the standard objections (and some not so standard ones)
Email to the author
, 2002
"... Part of the Biochemical and Biomolecular Engineering Commons, and the Biological Engineering Commons The complete bibliographic information for this item can be found at ..."
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Cited by 29 (0 self)
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Part of the Biochemical and Biomolecular Engineering Commons, and the Biological Engineering Commons The complete bibliographic information for this item can be found at
No margin, no mission? A field experiment on incentives for public service delivery”, forthcoming
- Journal of Public Economics.
, 2014
"... a b s t r a c t a r t i c l e i n f o We conduct a field experiment to evaluate the effect of extrinsic rewards, both financial and non-financial, on the performance of agents recruited by a public health organization to promote HIV prevention and sell condoms. In this setting: (i) non-financial re ..."
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Cited by 28 (6 self)
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a b s t r a c t a r t i c l e i n f o We conduct a field experiment to evaluate the effect of extrinsic rewards, both financial and non-financial, on the performance of agents recruited by a public health organization to promote HIV prevention and sell condoms. In this setting: (i) non-financial rewards are effective at improving performance; (ii) the effect of both types of rewards is stronger for pro-socially motivated agents; and (iii) both types of rewards are effective when their relative value is high. The findings illustrate that extrinsic rewards can improve the performance of agents engaged in public service delivery, and that non-financial rewards can be effective in settings where the power of financial incentives is limited.
A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators
- REVIEW OF ECONOMICS AND STATISTICS, FORTHCOMING
, 2011
"... The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known ..."
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Cited by 25 (2 self)
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The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations “as if” it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.
Supplement to “Agnostic notes on regression adjustments to experimental data: Reexamining Freedman’s critique.” DOI:10.1214/12-AOAS583SUPP
, 2013
"... (2008) 176–196] critiqued ordinary least squares regression adjustment of es-timated treatment effects in randomized experiments, using Neyman’s model for randomization inference. Contrary to conventional wisdom, he argued that adjustment can lead to worsened asymptotic precision, invalid measures o ..."
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Cited by 18 (3 self)
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(2008) 176–196] critiqued ordinary least squares regression adjustment of es-timated treatment effects in randomized experiments, using Neyman’s model for randomization inference. Contrary to conventional wisdom, he argued that adjustment can lead to worsened asymptotic precision, invalid measures of precision, and small-sample bias. This paper shows that in sufficiently large samples, those problems are either minor or easily fixed. OLS adjustment cannot hurt asymptotic precision when a full set of treatment–covariate in-teractions is included. Asymptotically valid confidence intervals can be con-structed with the Huber–White sandwich standard error estimator. Checks on the asymptotic approximations are illustrated with data from Angrist, Lang, and Oreopoulos’s [Am. Econ. J.: Appl. Econ. 1:1 (2009) 136–163] evaluation of strategies to improve college students ’ achievement. The strongest reasons to support Freedman’s preference for unadjusted estimates are transparency and the dangers of specification search. 1. Introduction. One
Trygve Haavelmo and the Emergence of Causal Calculus
, 2012
"... Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome, and lays out a logical framework for capturing the relationships between theory, data and policy questions. Th ..."
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Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome, and lays out a logical framework for capturing the relationships between theory, data and policy questions. The mathematical tools that emerge from this framework now enable investigators to answer complex policy and counterfactual questions using embarrassingly simple routines, some by mere inspection of the model’s structure. Several such problems are illustrated by examples, including misspecification tests, identification, mediation and introspection. Finally, we observe that modern economists are largely unaware of the benefits that Haavelmo’s ideas bestow upon them and, as a result, econometric research has not fully utilized modern advances in causal analysis. 1
